The underlying invention generally relates to the field of wireless communication systems with high-speed mobile access, especially to Orthogonal Frequency Division Multiplexing (OFDM) systems considering channel estimation and/or channel tracking. More particularly, the invention provides an adaptive subcarrier loading function for a mobile receiver in a wireless communication system based on OFDM that can advantageously be applied to predict the channel transfer function H(j·ω,t) of a multipath propagation channel being severely impaired by frequency-selective fading and an extremely time-variant behavior by detecting the position and/or movement of zero points of said transfer function H(j·ω,t), thereby reducing the probability of an incorrect assignment of the modulation scheme for each subcarrier, that is caused by mobile terminals moving at high velocity.
The development of wireless communication systems for high bit-rate data transmission and high-quality information exchange between terminals in indoor and outdoor environments is becoming the new research challenge in telecommunication area. Possible applications are mobile cellular systems, the Wireless Local Area Network (WLAN), the Wireless Local Loop (WLL), and others. In this connection, the underlying research activity aims at the performance evaluation of an adaptive multi-carrier modulation scheme (Adaptive Orthogonal Frequency Division Multiplexing, AOFDM) for wireless broadband indoor modems. The framework of AOFDM is the European project “WIND-FLEX” that aims to design and demonstrate a high-bit-rate flexible and configurable modem architecture, that provides wireless access to the Internet in an indoor environment where slow mobility is required (about 1 m/s). The system scenario is the one typical for domestic environments with a short range (within 20 meters). This scenario could be characterized by a set of terminals that needs to exchange data and to communicate with the external world. The requested modem platform has then to support different kinds of services, voice, data or video, with the possibility of transmitting both in a synchronous (for real-time applications) and an asynchronous way. A modem requirement is the capability of supporting variable bit rates in the range of 64 kBit/s to 100 MBit/s of payload, in order to create a multi-technological platform, available for different applications.
The frequency band around 2.4 GHz and 5 GHz have already been used by other wireless transmission standards, such as IEEE-802.11 and HiperLAN/2 and are close to saturation. For the WIND-FLEX system, the expectation of the 17 GHz unlicensed frequency band seems to be a promising and challenging solution. The whole available spectrum (17.1 to 17.3 GHz) will be divided into four 50 MHz-width channels, which are not simultaneously selectable. The considered AOFDM modulation scheme has been designed to efficiently transmit in one of these channels.
Before examining the applied transmission systems according to the state of the art, it is necessary to briefly describe the characteristics of the channel distortions mobile communication is faced with. Wireless environments are characterized by a variety of factors that severely impede reliable communication over a mobile radio channel. In general, the sources of degradation can be grouped into two categories: channel impairments and noise sources. On the one hand, a broadband radio channel, as needed for the transmission of high data rates, is characterized by severe attenuation fades (frequency-selective fading) caused by multipath propagation of the transmitted mobile radio signals. On the other hand, it exhibits a time-variant behavior due to the mobility of the receiver, which possibly requires a continuous adaptation of the transmission system to said behavior. Thereby, despite a plurality of differences, most wireless links share two common characteristics, time dispersion and time variability, which shall briefly be described in the following sections.
Wireless links can be described by the presence of multiple signal paths between the transmitter and the receiver. These multipath components are generated whenever signals are reflected by objects in the environment such as buildings, walls, ceilings, mountains, cars, people, etc. Differences in reflected path lengths cause impulsive signal transmissions to arrive at the receiver with a finite temporal scattering, which is called the root mean square (RMS) delay spread Δ of the multipath propagation channel. With the aid of Δ, the approximate duration of the channel “echoes” resulting from multipath arrivals can be measured.
Time-dispersive channels generate at least two potentially deleterious effects at the receiver, namely frequency-selective amplitude, phase variations and intersymbol interference (ISI). Frequency-dependent variations are caused by (randomly) delayed signal components adding out of phase at the receiver. Since the spectral location of fades is strongly dependent on the signal phase, the overall channel impulse response is highly sensitive to changes in the location and orientation of the receiver. Meanwhile, ISI occurs whenever delayed arrivals from one symbol interval “spill over” into subsequent symbol intervals. Thereby, ISI impedes the ability of the receiver to distinguish the desired signal from the echoes of previously transmitted symbols. The impact of both channel selectivity and ISI primarily depends on whether the system uses narrowband or wideband signaling.
Wireless channels, like other communication mediums, are subject to time-varying behavior. One of the distinguishing features of wireless links is the magnitude and rate at which these variations occur. An important measure of variability for a wireless channel is the coherence time Tcoh—the interval during which the impulse response of the multipath propagation channel remains correlated. The coherence time Tcoh can be approximated by the reciprocal value of the Doppler spread BD using a generalized channel model that explicitly incorporates the channel's time dependence:
                    T        coh            ≈                                    1                          B              D                                ⁡                      [            s            ]                          ⁢                                  ⁢        with        ⁢                                  ⁢                  B          D                      :=          2      ·                        f          D                ⁡                  [          Hz          ]                      ,                wherein fD denotes the Doppler shift of the channel.        
Thereby, Tcoh provides a measure of the rate at which variations in the wireless link occur. Channels are described as “fast fading” or “slow fading” depending on the length of the coherence time Tcoh relative to a single symbol interval: A slowly changing channel has a large coherence time Tcoh or, equivalently, a small Doppler spread BD, and vice versa. As can be expected, the channel coherence time Tcoh is strongly dependent on the rate of motion for the transmitter, receiver, and other objects in the environment. For narrowband signals, the fading rate directly affects the responsitivity and dynamic range requirements of the receiver. For wideband systems, the fading rate primarily impacts the required convergence rate for adaptive receiver algorithms. Wireless designs often guarantee adequate performance under “worst-case” conditions, by limiting the achievable performance under more favorable conditions. One solution would be to exploit time-varying channel knowledge to provide optimized time-varying performance. This approach requires both channel estimation and adaptive receiver implementation, but offers the promise of substantial performance gains. Of course, the larger and faster the link variations, the more difficult (and computationally intensive) the tasks of estimation and adaptation become. Hence, the receiver consumes more energy. Because channel modeling is an active area of wireless research, a wide variety of models—both empirical and statistical—have been developed to characterize the channel impairments described above.
In an indoor wireless channel, the dominant impairment is the fading, which is connected with a multipath propagation environment. Thereby, the electromagnetic waves are perturbed by structures, walls and furniture inside the building in such a way that the modulated signal propagates along several paths that connect the transmitter with the receiver. According to the diffuse multipath model, the received signal y(t) can be viewed as the composition of a continuum of signal replicas: When a narrowband signalx(t)=Re {{tilde over (x)}(t)·ej·2π·fc·t}having the complex envelope {tilde over (x)}(t) and the center frequency fc is transmitted, the received narrowband signaly(t)=Re {{tilde over (y)}(t)·ej·2π·fc·t}has a complex envelope {tilde over (y)}(t) which can be expressed by means of the following convolution integral:
                    y        ~            ⁡              (        t        )              =                                        x            ~                    ⁡                      (            t            )                          *                  h          ⁡                      (                          τ              ,              t                        )                              =                        ∫                      -            ∞                                +            ∞                          ⁢                                            h              ⁡                              (                                  τ                  ,                  t                                )                                      ·                                          x                ~                            ⁡                              (                                  t                  -                  τ                                )                                              ⁢                      ⅆ            τ                                ,wherein                h(τ,t) denotes the time-varying complex baseband impulse response of the underlying multipath propagation channel,        τrepresents the time delay, and        t represents the observation instant.        
It has been shown that the diffuse multipath model can be represented in baseband as a tapped-delay line (TDL) with time-varying complex coefficients and a fixed tap spacing 1/B, where B is the passband signal bandwidth. For practical reasons, the number of taps in the TDL is kept finite, and it is related to the delay spread of the fading channel. The tap gains are scaled according to the Power Delay Profile
                              R          c                ⁡                  (          τ          )                    ≡                        φ          h                ⁡                  (                      τ            ,                          Δ              ⁢                                                          ⁢              t                                )                      ⁢          |                        Δ          ⁢                                          ⁢          t                =        0              =                              1          2                ·        E            ⁢              {                                                        h              ⁡                              (                                  τ                  ,                  t                                )                                                          2                }              =                  lim                  T          →          ∞                    ⁢                        1                      2            ·            T                          ·                              ∫                                          -                T                            /              2                                      T              /              2                                ⁢                                                                                      h                  ⁡                                      (                                          τ                      ,                      t                                        )                                                                              2                        ⁢                          ⅆ              t                                                          (using Z*Z=Re{z}2+Im{z}2=|z|2∀z εC)wherein        Δt represents the difference in the observation instant t,        “*” denotes the complex conjugate operation, and        E{·} denotes the expectation over the time t.Thereby, the delay cross-power spectral density φh(τ, Δt) is defined as follows:        
                    φ        h            ⁡              (                  τ          ,                      Δ            ⁢                                                  ⁢            t                          )              ≡                            1          2                ·        E            ⁢              {                                            h              ′                        ⁡                          (                              τ                ,                t                            )                                ·                      h            ⁡                          (                              τ                ,                                  t                  +                                      Δ                    ⁢                                                                                  ⁢                    t                                                              )                                      }              =            lim              T        →        ∞              ⁢                  1                  2          ·          T                    ·                        ∫                                    -              T                        /            2                                T            /            2                          ⁢                                                            h                ′                            ⁡                              (                                  τ                  ,                  t                                )                                      ·                          h              ⁡                              (                                  τ                  ,                                      t                    +                                          Δ                      ⁢                                                                                          ⁢                      t                                                                      )                                              ⁢                                    ⅆ              t                        .                              The Power Delay Profile Rc(τ) characterizes the fading channel and measures the mean signal power relative to its dispersion across time. Several forms have been suggested for a decaying Power Delay Profile that models different fading channels. For a wide range of a frequencies and environments, including the 17 GHz indoor radio channel, the decaying Power Delay Profile could reasonable be described by an exponential distribution. Therefore, the considered Power Delay Profile is given by
            R      c        ⁡          (      τ      )        =      {                                                                      1                τ                            ·                              ⅇ                                                      -                    t                                    /                                      τ                    _                                                                                                                          for                ⁢                                                                  ⁢                τ                            ≥              0                                                            0                                otherwise                              ,      wherein τ denotes the mean delay. In general, τ is determined by the physical environments, and it is assumed to be about 50 ns for an indoor link at 17 GHz frequency band. The length of the TDL is determined by the delay spread Δ, which is defined as the range of τ for which the delay profile Rc(τ) is essentially non-zero. The length is therefore given by the nearest integer of Δ·B+1, wherein B is the passband signal bandwidth and Δ can reasonably assumed to be about 200 ns. The tap gains are independent complex Gaussian processes, whose variances are determined according to the Power Delay Profile Rc(τ).
Since the preferred embodiment of the underlying invention is directed to a pilot-assisted multi-carrier transmission system wherein Adaptive Orthogonal Frequency Division Multiplex (AOFDM) is applied, the basic aspects and principles of OFDM and adaptive loading techniques shall briefly be summarized in the following sections.
Conventional single-carrier modulation methods for the transmission at high symbol rates experience a severe limitation in time-dispersive and frequency-selective channels due to their sensitivity to ISI. To handle ISI, usually the entire bandwidth of the single-carrier signal has to be (adaptively) equalized by quite complex time-domain channel equalizers, e.g. Viterbi equalizers. Thereby, the complexity of a channel equalizer increases with the amount of ISI which has to be eliminated. If a high data rate of about 107 modulation symbols per second is transmitted over a radio channel having a maximum delay τmax of 10 μs, ISI extending over 100 modulation symbols might arise. For this reason, such an equalizer might be too expensive for an implementation.
If a conventional single-carrier transmission system is applied in an environment with severe transmission conditions, the channel equalization, which is supposed to eliminate the influence of the radio channel as far as possible, can be very extensive. The choice of an appropriate modulation technique for wireless data communication is therefore a critical issue due to the adverse influence of the dispersive and mostly time-variant mobile radio channel. In recent years, the interest in multi-carrier modulation for wireless transmission has been revived, whereas in former times the practicality of this concept appeared to be limited.
A promising approach to multi-carrier modulation which can easily be realized is Orthogonal Frequency Division Multiplexing (OFDM). OFDM offers advantages in transmission over severe multipath channels, so that there is an increased interest in applying OFDM in high-rate mobile or portable data transmission today. OFDM is a powerful technique that can advantageously be employed in communication systems suffering from frequency-selective distortion. Combined with multiple antennas at the transmitter and receiver as well as adaptive modulation, OFDM proves to be robust against channel delay spread. Furthermore, it leads to significant data rates with improved bit error performance over links having only a single antenna at both the transmitter and the receiver.
The main advantage of OFDM is that each sub-channel is relatively narrowband and is assumed to have flat fading. However, it is possible that a given sub-channel has a low power, which results in a large bit error ratio (BER). Thus, it is desirable to take advantage of sub-channels having relatively good performance, which is the motivation for adaptive modulation. In the context of time-varying channels, there is a decorrelation time associated with each frequency-selective channel instance. Thus, a new adaptation must be implemented each time the channel decorrelates. Since the channel is slowly time-varying, the receiver can provide reliable channel state information to its transmitter using a robust feedback channel. For this reason, loading modulation schemes according to the channel response of each subcarrier seems to be an interesting approach for increasing the capacity usage of the channel.
On the assumption that the transmitter knows the instantaneous channel transfer functions of all users simultaneously participating in different mobile communication sessions, many authors have demonstrated that significant performance improvement can be achieved if adaptive modulation is used together with OFDM. Thereby, adaptive modulation is an important technique that yields increased data rates over non-adaptive uncoded schemes. In general, subcarriers with large channel gains employ higher-order modulation to carry more bits per OFDM symbol, while subcarriers in deep fades carry one or even zero bits per symbol. Integrated design of forward error correction (FEC) and adaptive modulation using the Bose-Chadhuri-Hocquenghem (BCH) code and Trellis-Coded Modulation (TCM) has also been studied. Although both coding techniques consider only time-varying flat fading channels, the same coded adaptive modulation design can easily be applied to OFDM systems. As different subcarriers experience different fades and transmit different numbers of bits, the power level of the transmitted RF signal has to be changed accordingly.
When OFDM with adaptive modulation is applied in a frequency-selective fading channel, a significant portion of the subcarriers may not be used. These are typically subcarriers which experience deep fade and are not power-efficient to carry any information bits. In multiuser systems using static Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA) as multi-access schemes, each user is allocated a pre-determined time slot or frequency band, respectively, to apply OFDM with adaptive modulation. Consequently, these unused subcarriers (as a result of adaptive modulation) within the allocated time slot or frequency band of the respective user are wasted and can not be used by other users. However, those subcarriers which appear in deep fades to one user may not be in deep fade for other users. In fact, it is quite unlikely that a subcarrier will be in deep fade for all users, as the fading parameters for different users are mutually independent. This motivates to consider a so-called adaptive multiuser subcarrier allocation scheme. Thereby, subcarriers are assigned to the users based on instantaneous channel information. This approach will allow all subcarriers to be used more efficiently as subcarriers will only be left unused if they appear to be in deep fade to all users.
The main object of an adaptive subcarrier loading function is to assign the modulation scheme of each subcarrier according to the channel impulse response which can be determined by frequency-selective channel distortion. Thereby, for subcarriers around deep distortions, a lower modulation scheme such as BPSK is assigned, whereas for subcarriers without any severe distortion, a higher modulation scheme—e.g. Quadrature Amplitude Modulation (QAM) with a 16- or 64-point signal constellation—is assigned. For example, the communication system between an access point 401 (AP) and a mobile terminal 405 (MT) capable of executing this function comprises the following steps:                measurement of the channel transfer function H(j·ω,t),        creation of a modulation scheme assignment plan for each subcarrier according to the result of the respective channel impulse response measurement and negotiation between the AP 401 and the MT 405,        transmission of a signal by the AP 401 according to the applied modulation scheme assignment plan.        
In case an MT 405 is moving at high velocity, the channel transfer function H(j·ω,t) is changing fast. Compared to the changing of H(j·ω,t), the time duration between the timing of its measurement and the timing of a transmission according to a new modulation scheme assignment plan should be longer to guarantee a correct assignment. Otherwise, an incorrect assignment of the employed modulation scheme for said subcarriers might occur.